Liu Yingchao, Zhong Huohu, Dai Zhisen, Huang Yuxin, Liu Yibin, He Hefan, Liao Yuewen, Liu Weifeng
Department of Anesthesiology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, 350000, China.
Department of Anesthesiology, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, China.
BMC Anesthesiol. 2025 Feb 8;25(1):64. doi: 10.1186/s12871-025-02936-z.
To investigate the independent risk factors associated with postoperative nausea and vomiting (PONV) following Cesarean section procedures, and establish and validate a nomogram to predict them.
The clinical data of 116 adult patients who underwent Cesarean section procedures between August 2022 and February 2023 were included. Participants were randomly divided into training (n = 87) and verification sets (n = 29) in a 3:1 ratio. Univariate and multivariate logistic regression were used to analyze the risk factors for PONV following Cesarean sections and the independent risk factors were then used for the prediction model. Simultaneously, 29 adult patients who underwent caesarean section between February 2023 and April 2023 were included in the hospital as a test set to conduct external verification of the nomogram and Apfel scoring models, and compare their diagnostic efficacy in predicting PONV after caesarean section.
A history of motion sickness, systolic blood pressure reduction > 20%, and gastric volume were independent risk factors for PONV and used to construct the model. The AUC for predicting the risk of PONV in the training and validation sets was 0.814 (95% confidence interval [CI] = 0.709-0.918) and 0.792 (95% CI = 0.621-0.962), respectively. In the test set, the AUCs of the nomogram and the Apfel scoring models were 0.779 (95% CI = 0.593-0.965) and 0.547 (95% CI = 0.350-0.745), respectively, with the former being significantly higher (Z = 2.165, P < 0.05).
Our nomogram model was superior to the Apfel scoring model and may be helpful in formulating appropriate individualized management strategies for nausea and vomiting following Cesarean sections, to promote the rapid recovery of patients.
探讨剖宫产术后恶心呕吐（PONV）的独立危险因素，并建立和验证预测其发生的列线图。
纳入2022年8月至2023年2月期间行剖宫产手术的116例成年患者的临床资料。参与者按3:1的比例随机分为训练集（n = 87）和验证集（n = 29）。采用单因素和多因素logistic回归分析剖宫产术后PONV的危险因素，然后将独立危险因素用于预测模型。同时，纳入2023年2月至2023年4月期间在本院行剖宫产的29例成年患者作为测试集，对列线图和Apfel评分模型进行外部验证，并比较它们在预测剖宫产术后PONV方面的诊断效能。
晕动病史、收缩压下降>20%和胃内容量是PONV的独立危险因素，并用于构建模型。训练集和验证集中预测PONV风险的AUC分别为0.814（95%置信区间[CI]=0.709-0.918）和0.792（95%CI=0.621-0.962）。在测试集中，列线图和Apfel评分模型的AUC分别为0.779（95%CI=0.593-0.965）和0.547（95%CI=0.350-0.745），前者显著更高（Z=2.165，P<0.05）。
我们的列线图模型优于Apfel评分模型，可能有助于制定剖宫产术后恶心呕吐的个体化管理策略，促进患者快速康复。
